Uncertainty Quantification is the process by which uncertainties in a system are characterized and propagated to a given Quantity of Interest.
Verification is the process of determining whether a computational model and its implementation produce predictions with sufficient accuracy, in other words, whether the difference (the error) between the exact (unavailable) and approximate solutions of the model is sufficiently small.
RCFD UQ based simulation for designing clean internal combustion engines, industrial burners, among others.
In this application thrust we develop stochastic based algorithms to significantly reduce the power consumption of wireless communication systems.
We develop adaptive schemes and reduced-order modeling techniques for generating efficient and accurate Sorogate Models, which will enable the use of Collocation-based gPC methods in large-scale stochastic EM simulations.